Abstract
Background
Cognitive reserve (CR) is the mismatch between preserved cognition and neuropathological damage. Amyloidopathy in Parkinson's disease (PD) could be associated with faster progression to dementia, but the putative protective effect of CR is unknown.
Objectives
To evaluate the effect of CR on β‐amyloid burden and brain metabolism in non‐demented PD subjects.
Methods
Participants with PD (n = 53) underwent a clinical evaluation, [18F]‐fluorodeoxyglucose and [18F]‐flutemetamol positron emission tomography magnetic resonances, and were classified according to CR. The metabolic pattern of 16 controls was compared to PD subjects.
Results
The PD subjects showed hypometabolism mainly in the bilateral posterior cortex. Superior‐CR subjects (n = 22) exhibited better cognitive performance, increased amyloid burden, and higher metabolism in several right hemisphere areas compared to low‐medium‐CR subjects (n = 31).
Conclusions
Higher CR in non‐demented PD is associated with better cognitive performance, which might reduce vulnerability to the effect of β‐amyloid. Whether superior CR leads to protection against metabolic deterioration, and predominantly right hemisphere involvement, deserves further exploration.
Keywords: amyloid, cognition, cognitive reserve, metabolism, Parkinson's disease
The concept of cognitive reserve (CR) refers to a mismatch between relatively preserved cognition and the severity of brain pathology found in autopsy studies in non‐demented subjects. 1 CR has been proposed to be a protective factor that buffers the effect of brain damage on cognition 2 and has been widely studied in different phases of Alzheimer's disease (AD). 3 Most cross‐sectional studies have shown that subjects with higher CR had higher levels of global pathological damage at similar levels of cognitive performance. 3 Longitudinal amyloid‐positron emission tomography (PET) studies have also shown that higher CR was associated with better cognitive performance independent of the amyloid burden. 4
Parkinson's disease (PD) is the second most common neurodegenerative disease. 5 , 6 In addition, after 18 years most patients develop dementia. 7 Higher CR in PD has been found to be associated with lower motor impairment, 8 better cognitive performance, 9 , 10 , 11 and slower cognitive decline. 8 A previous study in PD 12 described an association between worse cognitive performance and higher cortical amyloid burden in subjects with <16 years of education, but by contrast, there was no correlation between cortical amyloid binding and cognition in subjects with ≥16 years of education. No previous studies in PD have evaluated the relationship between CR with brain metabolism, amyloid deposition, and cognitive performance. Most studies in PD have used years of education or intelligence quotient as proxies for CR. In this study, we used the Cognitive Reserve Questionnaire (CRQ) 13 with the purpose of including a variety of aspects related to CR. We aimed to explore the relationship in non‐demented PD subjects between: (1) CR and cognitive performance; (2) CR and amyloid‐PET uptake; (3) CR and metabolic activity measured by [18F]‐fluorodeoxyglucose (FDG)‐PET; and (4) correlations between CR and amyloid‐PET uptake and FDG‐PET.
Methods
Subjects
Healthy controls (HC) and non‐demented subjects with late onset (>50 years) PD (to avoid the young‐onset PD profile), ages <80 years, and <10 years of disease were included. Participants with other neurological disorders, severe depression (Geriatric Depression Scale >20), magnetic resonance imaging (MRI) abnormalities, or other causes of cognitive decline were excluded. The study was approved by the Research Ethics Board at HM‐Hospitales, and informed consent was obtained from all participants.
Participants were recruited at the Centro Integral de Neurociencias AC/University Hospital HM Puerta del Sur, in Móstoles (Spain). The diagnosis of PD was made according to the United Kingdom Brain Bank Clinical Criteria, 14 and dementia was excluded based on Clinical Diagnostic Criteria for PD Dementia. 15 Evaluations included a comprehensive neuropsychological battery and the Movement Disorder Society‐Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS‐UPDRS‐III, motor severity). HC were healthy volunteers without neurological or psychiatric history, whose preserved cognitive state was ascertained by a comprehensive neuropsychological battery.
Neuropsychological Assessment and CR Evaluation
Cognitive tests were conducted on all participants by a neuropsychologist. PD subjects were tested in the on‐medication state. Attention (Digit Span Forward and Trail Making Test A [TMT A]), 16 , 17 executive function (Trail Making Test B [TMT B] and Stroop Interference), 17 , 18 language (Semantic Fluency and Boston Naming Test), 19 , 20 visuospatial function (Benton Judgment of Line Orientation and Visual Object and Space Perception Silhouettes), 21 , 22 verbal memory (Consortium to Establish a Registry for Alzheimer's disease delayed recall) 23 and visual memory (Wechsler Memory Scale delayed recall) 24 were explored. TMT B–TMT A 25 was estimated to reduce the motor component of the test in the set‐shifting measurement. The cognitive diagnosis was made by consensus between two neurologists with expertise in cognition and one neuropsychologist, based on the results of cognitive tests, the Emre criteria, 15 and the Pfeffer Functional Activities Questionnaire administered to an informant. 26 CR was estimated using the CRQ, 13 which explores different aspects of education and intellectual activities (education, parent's education, training courses, work occupation, musical training, languages, reading activity, and intellectual games). The total score ranges between 0 and 25. The normative data of the CRQ are determined on quartiles, defining the CR level as follows: ≤6 meaning inferior CR, 7–9 medium‐low, 10–14 medium‐high, and ≥15 superior. Therefore, the subjects from the study were classified as superior‐CR for scores ≥15 or as low‐medium‐CR for scores <15.
PET‐Magnetic Resonance Scans
Imaging data were acquired on a hybrid 3TmMR‐Biograph system (Siemens Healthcare, Erlangen/Germany). All PD subjects underwent [18F]‐flutemetamol PET acquisition following a 90‐minute uptake period after intravenous injection of 185 MBq of the radiopharmaceutical to estimate amyloid deposition. On a separate day, all subjects were studied with FDG during the off‐medication state, after at least 6 hours of fasting and with a serum glucose level <8 mmol/L. PET scans were acquired 40 minutes after intravenous injection of 5 MBq/kg of FDG. Simultaneous T1‐weighted MRI scans were acquired in each session and normalized to the MNI space using the unified segmentation method in statistical parametric mapping (SPM12). 27 All PET studies were corrected for partial volume effect using the modified Müller‐Gärtner method, 28 normalized to the Montreal Neurological Institute space by applying the transformations obtained for MRI, and smoothed using an 8 mm full width at half maximum kernel to be more restrictive on possible head motion artifacts. Voxelwise standardized uptake value ratio maps were generated using the cerebellar cortex as reference region. To verify the feasibility of this ratio normalization, we estimated the differences between residuals from model estimation using parametric voxel‐based statistics.
Statistical Analysis
In continuous and normally distributed variables, analysis of variance with post‐hoc Bonferroni multiple comparison or t test was applied. For non‐normally distributed variables, the Kruskal‐Wallis and Mann–Whitney‐U tests were used. A χ2 test was applied for categorical variables. Statistical analyses were performed with SPSS21. Significance was set at P < 0.05.
Voxelwise statistical analysis (SPM12) was conducted first for FDG comparisons between PD subjects and HC. Second, Flutemetamol and FDG uptake was compared between superior‐ and low‐medium‐CR subjects. Age was incorporated as a covariate of interest. Finally, we performed a voxelwise correlation analysis of CR score with amyloid burden and metabolism. A significance threshold of P < 0.001 was applied, uncorrected for multiple comparisons at voxel level. A minimum cluster size was selected for each test to obtain cluster‐level family‐wise error correction based on SPM12 Gaussian random field theory, corrected at the cluster threshold of P < 0.05.
Results
Fifty‐three PD subjects and 16 HC were included in the study. Twenty‐two subjects were classified as superior‐CR and 31 as low‐medium‐CR. No differences existed between HC and PD subjects, nor between the two groups of PD subjects in terms of the clinical and demographic variables (Table S1).
Subjects with superior‐CR showed better performance in all cognitive domains, with significant differences in all tests except Stroop Interference and a trend toward significance in silhouettes test (Table 1). Three PD subjects with superior‐CR (13.6%) and 14 with low‐medium‐CR (42.5%) met the criteria for mild cognitive impairment according to level II MDS task force guidelines. 29
TABLE 1.
Results of neuropsychological assessment
| Low‐medium | Superior | Healthy | P value | |
|---|---|---|---|---|
| CR | CR | Controls | ||
| n = 31 | n = 22 | n = 16 | ||
| Attention | ||||
| Digit span forward | 5.03 (1.26)# | 6.00 (1.23) | 5.69 (0.95) | <0.05 |
| TMT A | 45.42 (16.14)*, # | 33.14 (13.17) | 32.06 (11.38) | <0.05 |
| Executive function | ||||
| TMT B | 142.48 (71.26)*, # | 87.00 (48.28) | 80.69 (23.97) | <0.05 |
| Stroop interference | 75.32 (22.0)* | 65.59 (16.55)* | 54.38 (6.60) | <0.05 |
| TMT B–TMT A | 94.7 (61.70)*, # | 53.9 (40.15) | 48.63 (23.68) | <0.05 |
| Language | ||||
| Semantic fluency | 16.68 (5.0)*, # | 21.27 (7.94) | 23.31 (5.95) | <0.05 |
| Boston naming test | 52.87 (4.03)*, # | 55.09 (6.67) | 55.88 (3.28) | 0.12 |
| Visuospatial | ||||
| Benton JLO | 21.00 (4.0)*, # | 25.50 (2.77) | 25.88 (3.18) | <0.05 |
| VOSP silhouettes | 22.81 (3.12)* | 24.14 (4.31) | 24.81 (2.64) | 0.09 |
| Memory | ||||
| Verbal memory | ||||
| CERAD | 4.39 (2.03)*, # | 6.5 (2.09) | 7.19 (1.52) | <0.05 |
| Visual memory | ||||
| WMS‐IV | 17.45 (7.78)*, # | 25.50 (11.38) | 27.06 (5.17) | <0.05 |
Note: Data are listed as mean (standard deviation).
Abbreviations: CR, cognitive reserve; TMT‐A, Trail Making Test A; TMT‐B, Trail Making Test B; Benton JLO, judgment line orientation; VOSP silhouettes, visual object and space perception; CERAD delayed recall, Consortium to Establish a Registry for Alzheimer's Disease, WMS‐IV delayed recall, Wechsler Memory Scale 4th edition.
P < 0.05 vs. healthy controls;
P < 0.05 vs. superior CR.
Regional Differences in FDG PET‐Magnetic Resonance and [ 18F]‐Flutemetamol PET‐Magnetic Resonance
In keeping with previous findings in PD patients, 30 , 31 voxelwise comparison analyses revealed significant hypometabolism in the temporal and parieto‐occipital cortex bilaterally and to a lesser extent in the frontal cortex in the PD group in comparison with HC (Fig. S1).
The subgroup of PD subjects with superior‐CR showed higher metabolism in the fusiform gyrus, temporal middle, occipital inferior, and parietal inferior cortices on the right side compared with subjects with low‐medium‐CR (Fig. 1 and Table S2).
FIG. 1.
Voxelwise differences in amyloid burden (warm colors) and glucose metabolism (cool colors) between superior and low‐medium cognitive reserve groups. (A) Increased uptake in [18F]‐flutemetamol in association with superior cognitive reserve. (B) Increased metabolism in superior cognitive reserve groups measured by [18F]‐Fluorodeoxyglucose uptake. Data are thresholded at uncorrected P < 0.001, family‐wise error corrected at cluster level P < 0.05.
Amyloid burden was higher in superior‐CR subjects compared to low‐medium‐CR in the temporal middle cortex, anterior cingulate, and frontal inferior triangular cortex of the right hemisphere (Fig. 1 and Table S2).
We found a positive correlation (P < 0.001, family‐wise error corrected at cluster level) between FDG uptake and CR in the occipitotemporal region, comprising the right middle and inferior temporal, lingual, and fusiform gyri (Fig. S2 and Table S3). We saw no evidence of association between Flutemetamol uptake and CR.
Discussion
In this study, we explored the relationship between CR with β‐amyloid distribution and brain metabolism in non‐demented PD subjects. As expected, 8 PD subjects with superior‐CR had better performance in all cognitive domains. We also found that subjects with superior‐CR exhibited higher amyloid uptake as well as higher metabolism in comparison to low‐medium‐CR. Our findings are potentially relevant to a better understanding of the evolution of cerebral changes in PD and the influence of CR.
Regarding the cognitive state, the proportion of patients being classified as mild cognitive impairment (MCI) was superior in the low‐medium CR group compared to superior CR participants. This was something expected, because the diagnosis of PD‐MCI is based on cognitive performance according to age and educational level. Because educational level is part of CR, we consider that classifying these patients according to the presence of MCI would not be appropriate, because we would be posing a dependency in which the dependent variable is the one that determines the value of the independent variable. In addition, previous works in the general population 32 and in PD 8 , 10 , 33 have shown that patients with higher CR had better cognitive performance. Therefore, the imbalance between the two groups is inherent in the CR itself. We want to emphasize the importance of other aspects of CR in the evaluation of cognitive outcomes, since education seems to be only one component of the complex construct that makes up the CR. Abnormal amyloid deposition is recognized as a risk factor for developing cognitive impairment in PD and faster progression to dementia. 34 , 35 Indeed, the association of synucleinopathy and AD pathology is the most robust pathological correlate of dementia in PD. 36 Furthermore, there is solid evidence that indicates amyloid changes precede cerebral hypometabolism in AD dementia. 37
Moreover, the relationship between CR and cortical β‐amyloid accumulation in PD has only been examined previously in one study. 12 It reported that cortical β‐amyloid accumulation was predictive of cognitive impairment in subjects with low education, but this proxy for CR misses other important aspects that make up CR. In our study, subjects with superior‐CR compared to low‐medium‐CR had more amyloid burden, which suggests that higher CR increases resilience to the deleterious effects of amyloid deposition. In fact, we found no correlation between CR and amyloid burden. This supports the conclusion that higher CR does not lead to higher amyloid accumulation and that PD subjects with higher CR might compensate and be protected from pathological damage, perhaps via utilization of alternative networks. 38
Our findings about the relationship between metabolic changes and CR in PD are intriguing. FDG‐PET studies have been widely used to study cognitive impairment in PD, and hypometabolic patterns have been shown to be closely related and predictive of dementia and MCI. 30 , 31 Our non‐demented PD subjects had hypometabolism mainly in posterior areas compared to HC, which also has been well documented as an early sign of parietal‐occipital‐temporal involvement in the evolution of PD. 30 , 39 However, when comparing PD subjects according to their CR, relative hypermetabolism in posterior right cortical areas was shown in subjects with superior‐CR. The more preserved metabolism in this group of subjects, even in the presence of greater pathological damage may also be related to mechanisms whereby the cortex is less vulnerable and, therefore, somehow relatively “protected” from synaptic loss, as represented by hypometabolism. 40 Increased metabolism has been shown in highly educated MCI patients in comparison with low educated patients in AD. 41 Indeed, there was a positive correlation between CR and metabolism in the right occipitotemporal region in our PD subjects. Previous investigations have also described this correlation in HC in the medial frontal and temporal lobe of the right hemisphere 42 and in the left frontal orbital cortex, the right paracingulate/anterior cingulate, and the left frontal lobe in MCI patients. 41 The different distribution in these studies might reflect differences in methodological approaches and in clinical diagnosis that may be associated with differences in the distribution of pathology. It is, therefore, tempting to suggest that intellectual enrichment leads to higher cortical metabolic activity, which possibly plays a protective role in disease progression and resistance to brain pathology.
Concerning the specific regions of metabolic differences defined in our study, the right parietal, occipital, and temporal cortices have been described as vulnerable regions in cognitive impairment in PD. They show hypometabolism and then atrophy in a consecutive stage. 39 , 43 Therefore, it seems that higher CR may somehow provide protection from more severe hypometabolism in these areas.
Investigations of cerebral metabolism at rest in normal aging showed a negative association between a proxy of cognitive reserve combining education and intelligence and metabolic activity in temporoparietal areas. 44 By contrast, functional studies during memory tasks showed functional reorganization of brain networks (compensation) in healthy elders with higher education compared to young individuals 45 , 46 and more efficient or optimal patterns of brain activation in elders with higher reserve proxies compared to elders with lower reserve proxies. 47 , 48
Indeed, a previous study in HC with higher education found an increased regional cortical thickness in temporal areas and cingulate cortex, compared to HC with lower education. 49 In addition, a recent study showed higher amyloid burden according to florbetapir PET in mild cognitive impairment subjects with higher education (in frontal, temporal, and parietal regions) as well as increased metabolism in these same areas. 41 The affected areas from that study differ from the ones we found, likely because they are different diseases, the patients show different degree of cognitive performance, different covariates, different CR approaches, and the use of education as a continuous variable, not as dichotomization. Despite this, the fact that there is a higher relative metabolism in the areas of amyloid deposits may be explained as a compensatory effect or simply as a more preserved metabolism secondary to the resistance provided by a higher CR. Three different hypotheses have been put forward relating CR to amyloid PET and FDG PET findings in AD. The first hypothesis is that CR delays the onset of the disease, the second is that CR delays amyloid deposition, and the last is that CR poses a resilience to amyloid, which could be expressed with preserved metabolism. 50 Our findings are in line with this last point.
The fact that all metabolic and amyloid differences were found in the right hemisphere is also most intriguing. Considering that there were no differences in motor side predominance in this sample of PD patients, this finding fits with the hypothesis about the laterality of CR to this hemisphere. 51 In this regard, higher education level showed a significant association with higher gray matter volume 52 and higher metabolism in the right hemisphere 42 in healthy older adults. Our data do not allow any real interpretation or hypothesis, but they certainly are an interesting finding with potential relevance to understand cortical vulnerability associated with dementia.
Admittedly, this study has the limitations of its cross‐sectional nature and the small sample, which could affect the power of the analyses. Yet the sample size does not differ from previous neuroimaging works. 53 Moreover, the main strengths of the study were the use of both PET tracers, the comprehensive neuropsychological assessment, and administration of an accurate proxy of CR. 13 In addition, we evaluated a homogeneous group of PD subjects in terms of disease duration and age of onset, because early‐onset PD patients were excluded because of their lower risk of dementia.
In summary, non‐demented PD subjects with superior‐CR showed a better cognitive state in all cognitive domains compared to low‐medium‐CR subjects. They also had a higher amyloid burden and higher metabolism in several brain areas. Overall, our results suggest that superior‐CR in non‐demented PD patients could modify the vulnerability to the deleterious effect of amyloid burden on cognition and leads to less severe hypometabolism.
Author Roles
(1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the First Draft, B. Review and Critique.
B.F.R.: 1B, 1C, 2A, 2B, 2C, 3A
R.R.R.: 1C, 2A, 2C, 3B
P.G.: 1C, 3B
S.A.P.: 2A, 2C, 3B
C.T.: 1C, 3B
D.M.M.: 1C, 3B
I.O.: 1C, 3B
L.V.: 1C, 3B
I.P.L.: 1C, 3B
J.A.O.: 1B, 1C, 2C, 3B
C.G.S.: 1A, 1B, 1C, 2A, 2C, 3B
Disclosures
Ethical Compliance Statement: The study was approved by the Research Ethics Board at HM‐Hospitales, and informed consent was obtained from all participants. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines.
Funding Sources and Conflict of Interest: PET‐magnetic resonance studies were funded by the collaboration agreement between General Electric, Siemens Health‐care S.L.U., HM Hospitales 1989 S.A., and Fundación de Investigación HM Hospitales. The authors declare that there are no conflicts of interest relevant to this work.
Financial Disclosures for the Previous 12 months: C.G.S. received honoraria from Exeltis and from the Italian Society Parkinson and Movement Disorders (scientific lectures). J.A.O. received honorarium and traveling grants from BIAL Spain for lecturing at the Spanish Neurological Society annual meeting and received honorarium for lecturing in scientific meetings and traveling grants from Insightec and Esteve Pharmaceuticals. He has received consulting honorarium from Biogen or participating at Adverse Events Advisory Board 2023, and consulting honorarium from Roche and Bayern for attending one Advisory Board for each. He also holds several non‐paid, non‐profit research grants from the Spanish Ministry of Education and Science, Focused Ultrasound Foundation, and ASAP coalition. B.F.R., R.R.R., P.G., S.A.P., C.T., D.M.M., I.O., L.V., and I.P.L. report no further financial disclosures.
Supporting information
FIG. S1. Voxelwise differences in the [18F]‐Fluorodeoxyglucose PET‐MR scan between healthy controls and PD subjects. Data are thresholded at uncorrected P < 0.001, FWE corrected at cluster level P < 0.05.
FIG. S2. Positive correlations between cognitive reserve score and [18F]‐Fluorodeoxyglucose PET uptake in PD subjects. (Uncorrected P < 0.001, FWE corrected at cluster level P < 0.05), projected onto the right‐hemisphere cortical surface of a template in MNI space.
TABLE S1. Clinical and demographic data. Data are presented as mean (standard deviation) or frequency (number). CR, Cognitive Reserve; CRQ, Cognitive Reserve Questionnaire, MDS‐UPDRS III, Movement Disorder Society‐Unified Parkinson's Disease Rating Scale part III. *p < 0.05 vs Healthy Controls; #P < 0.05 vs Superior CR.
TABLE S2. Brain regions showing differences in amyloid load and metabolic load between low‐medium and superior cognitive reserve groups.
TABLE S3. Brain regions with significant positive correlation between glucose metabolism and cognitive reserve.
Relevant disclosures and conflict of interest are listed at the end of this article.
References
- 1. Katzman R, Terry R, DeTeresa R, et al. Clinical, pathological, and neurochemical changes in dementia: a subgroup with preserved mental status and numerous neocortical plaques. Ann Neurol 1988;23:138–144. [DOI] [PubMed] [Google Scholar]
- 2. Stern Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 2002;8:448–460. [PubMed] [Google Scholar]
- 3. Rentz DM, Mormino EC, Papp KV, Betensky RA, Sperling RA, Johnson KA. Cognitive resilience in clinical and preclinical Alzheimer's disease: the association of amyloid and tau burden on cognitive performance. Brain Imaging Behav 2017;11:383–390. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Soldan A, Pettigrew C, Cai Q, et al. Cognitive reserve and long‐term change in cognition in aging and preclinical Alzheimer's disease. Neurobiol Aging 2017;60:164–172. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Aarsland D, Kurz MW. The epidemiology of dementia associated with Parkinson disease. J Neurol Sci 2010;15(289):18–22. [DOI] [PubMed] [Google Scholar]
- 6. Erkkinen MG, Kim MO, Geschwind MD. Clinical neurology and epidemiology of the major neurodegenerative diseases. Cold Spring Harb Perspect Biol 2018;2(10):a033118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Hobson P, Meara J. Mortality and quality of death certification in a cohort of patients with Parkinson's disease and matched controls in North Wales, UK at 18 years: a community‐based cohort study. BMJ Open 2018;8:e018969. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Guzzetti S, Mancini F, Caporali A, Manfredi L, Daini R. The association of cognitive reserve with motor and cognitive functions for different stages of Parkinson's disease. Exp Gerontol 2019;115:79–87. [DOI] [PubMed] [Google Scholar]
- 9. Ciccarelli N, Monaco MRL, Fusco D, et al. The role of cognitive reserve in cognitive aging: what we can learn from Parkinson's disease. Aging Clin Exp Res 2017;30:1–4. [DOI] [PubMed] [Google Scholar]
- 10. Hindle JV, Hurt CS, Burn DJ, Brown RG, Samuel M, Wilson KC, Clare L. The effects of cognitive reserve and lifestyle on cognition and dementia in Parkinson's disease—a longitudinal cohort study. Int J Geriatr Psychiatry 2016;31:13–23. [DOI] [PubMed] [Google Scholar]
- 11. Cohen OS, Vakil E, Tanne D, Nitsan Z, Schwartz R, Hassin‐Baer S. Educational level as a modulator of cognitive performance and neuropsychiatric features in Parkinson disease. Cogn Behav Neurol 2007;20:68–72. [DOI] [PubMed] [Google Scholar]
- 12. Lucero C, Campbell MC, Flores H, Maiti B, Perlmutter JS, Foster ER. Cognitive reserve and β‐amyloid pathology in Parkinson disease. Parkinsonism Relat Disord 2015;21:899–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Rami L, Valls‐Pedret C, Bartrés‐Faz D, et al. Cuestionario de Reserva cognitiva. Valores obtenidos en población anciana sana y con enfermedad de Alzheimer [Cognitive reserve questionnaire. Scores obtained in a healthy elderly population and in one with Alzheimer's disease]. Rev Neurol 2011;52:195–201. [PubMed] [Google Scholar]
- 14. Hughes AJ, Daniel SE, Kilford L, Lees AJ. Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico‐pathological study of 100 cases. J Neurol Neurosurg Psychiatry 1992;55:181–184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Emre M, Aarsland D, Brown R, et al. Clinical diagnostic criteria for dementia associated with Parkinson's disease. Mov Disord 2007;22:1689–1707. [DOI] [PubMed] [Google Scholar]
- 16. Wechsler D. WAIS‐IV. Escala de inteligencia de Wechsler para adultos‐IV. Manual de aplicación y corrección. Vol 2008. Madrid: NCS Pearson, Inc. Edición original; 2012. [Google Scholar]
- 17. Partington J, Leiter R. Partington's pathway test. Psychol Serv Cent J 1949;1:11–20. [Google Scholar]
- 18. Golden CJ . Stroop Color and Word Test: A Manual for Clinical and Experimental Uses. Wood Dale, IL: Stoelting Company; 1978: 24. [Google Scholar]
- 19. Isaacs B, Kennie AT. The set test as an aid to the detection of dementia in old people. Br J Psychiatry 1973;123:467–470.o. [DOI] [PubMed] [Google Scholar]
- 20. Kaplan EF, Goodglass H, et al., eds. Boston naming test. Philadelphia: Lippincott Williams & Wilkins; 1983. [Google Scholar]
- 21. Benton AL, Sivan AB, de Hamsher K, Varney NR, Spreen O. Contributions to Neuropsychological Assessment. New York: Oxford; 1994. [Google Scholar]
- 22. Rapport LJ, Millis SR, Bonello PJ. Validation of the Warrington theory of visual processing and the visual object and space perception battery. J Clin Exp Neuropsychol 1998;20:211–220. [DOI] [PubMed] [Google Scholar]
- 23. Morris JC, Heyman A, Mohs RC, et al. The consortium to establish a registry for Alzheimer's disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer's disease. Neurology 1989;39(9):1159–1165. [DOI] [PubMed] [Google Scholar]
- 24. Wechsler D. Escala de Memoria de Wechsler. Madrid: Pearson educación, S.A; 2013. [Google Scholar]
- 25. Drane DL, Yuspeh RL, Huthwaite JS, Klingler LK. Demographic characteristics and normative observations for derived‐trail making test indices. Neuropsychiatry Neuropsychol Behav Neurol 2002;15:39–43. [PubMed] [Google Scholar]
- 26. Pfeffer RI, Kurosaki TT, Harrah CH Jr, Chance JM, Filos S. Measurement of functional activities in older adults in the community. J Gerontol 1982;37:323–329. [DOI] [PubMed] [Google Scholar]
- 27. Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage 2007;38:95–113. [DOI] [PubMed] [Google Scholar]
- 28. Müller‐Gärtner HW, Links JM, Prince JL, et al. Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI‐based correction for partial volume effects. J Cereb Blood Flow Metab 1992;12:571–583. [DOI] [PubMed] [Google Scholar]
- 29. Litvan I, Goldman JG, Tröster AI, et al. Diagnostic criteria for mild cognitive impairment in Parkinson's disease: Movement Disorder Society task force guidelines. Mov Disord 2012;27:349–356. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Firbank MJ, Yarnall AJ, Lawson RA, et al. Cerebral glucose metabolism and cognition in newly diagnosed Parkinson's disease: ICICLE‐PD study. J Neurol Neurosurg Psychiatry 2017;88:310–316. [DOI] [PubMed] [Google Scholar]
- 31. Garcia‐Garcia D, Clavero P, Gasca Salas C, et al. Posterior parietooccipital hypometabolism may differentiate mild cognitive impairment from dementia in Parkinson's disease. Eur J Nucl Med Mol Imaging 2012;39:1767–1777. [DOI] [PubMed] [Google Scholar]
- 32. Rodriguez FS, Zheng L, Chui HC, Aging Brain: Vasculature, Ischemia, and Behavior Study . Psychometric characteristics of cognitive reserve: How high education might improve certain cognitive abilities in aging. Dement Geriatr Cogn Disord 2019;47:335–344. [DOI] [PubMed] [Google Scholar]
- 33. Koerts J, Tucha L, Lange KW, Tucha O. The influence of cognitive reserve on cognition in Parkinson's disease. J Neural Transm (Vienna) 2013;120:593–596. [DOI] [PubMed] [Google Scholar]
- 34. Irwin DJ, Grossman M, Weintraub D, et al. Neuropathological and genetic correlates of survival and dementia onset in synucleinopathies: a retrospective analysis. Lancet Neurol 2017;16:55–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Sabbagh MN, Adler CH, Lahti TJ, et al. Parkinson disease with dementia: comparing patients with and without Alzheimer pathology. Alzheimer Dis Assoc Disord 2009;23:295–297. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Compta Y, Parkkinen L, O'Sullivan SS, et al. Lewy – and Alzheimer‐type pathologies in Parkinson's disease dementia: which is more important? Brain 2011;134:1493–1505. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Jack CR Jr, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013;12:207–216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Morbelli S, Perneczky R, Drzezga A, et al. Metabolic networks underlying cognitive reserve in prodromal Alzheimer disease: a European Alzheimer disease consortium project. J Nucl Med 2013;54:894–902. [DOI] [PubMed] [Google Scholar]
- 39. González‐Redondo R, García‐García D, Clavero P, et al. Grey matter hypometabolism and atrophy in Parkinson's disease with cognitive impairment: a two‐step process. Brain 2014;137:2356–2367. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Chételat G, Desgranges B, Landeau B, et al. Direct voxel‐based comparison between grey matter hypometabolism and atrophy in Alzheimer's disease. Brain 2008;131:60–71. [DOI] [PubMed] [Google Scholar]
- 41. Arenaza‐Urquijo EM, Bejanin A, Gonneaud J, et al. Association between educational attainment and amyloid deposition across the spectrum from normal cognition to dementia: neuroimaging evidence for protection and compensation. Neurobiol Aging 2017;59:72–79. [DOI] [PubMed] [Google Scholar]
- 42. Yoshizawa H, Gazes Y, Stern Y, Miyata Y, Uchiyama S. Characterizing the normative profile of 18F‐FDG PET brain imaging: sex difference, aging effect, and cognitive reserve. Psychiatry Res 2014;221:78–85. [DOI] [PubMed] [Google Scholar]
- 43. Harding AJ, Broe GA, Halliday GM. Visual hallucinations in Lewy body disease relate to Lewy bodies in the temporal lobe. Brain 2002;125:391–403. [DOI] [PubMed] [Google Scholar]
- 44. Bastin C, Yakushev I, Bahri MA, et al. Cognitive reserve impacts on inter‐individual variability in resting‐state cerebral metabolism in normal aging. Neuroimage 2012;1(63):713–722. [DOI] [PubMed] [Google Scholar]
- 45. Scarmeas N, Zarahn E, Anderson KE, et al. Association of life activities with cerebral blood flow in Alzheimer disease: implications for the cognitive reserve hypothesis. Arch Neurol 2003;60:359–365. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Springer MV, McIntosh AR, Winocur G, et al. The relation between brain activity during memory tasks and years of education in young and older adults. Neuropsychology 2005;19:181–192. [DOI] [PubMed] [Google Scholar]
- 47. Solé‐Padullés C, Bartrés‐Faz D, Junqué C, et al. Brain structure and function related to cognitive reserve variables in normal aging, mild cognitive impairment and Alzheimer's disease. Neurobiol Aging 2009;30:1114–1124. [DOI] [PubMed] [Google Scholar]
- 48. Bosch B, Bartrés‐Faz D, Rami L, et al. Cognitive reserve modulates task‐induced activations and deactivations in healthy elders, amnestic mild cognitive impairment and mild Alzheimer's disease. Cortex 2010;46:451–461. [DOI] [PubMed] [Google Scholar]
- 49. Liu Y, Julkunen V, Paajanen T, et al. Education increases reserve against Alzheimer's disease—evidence from structural MRI analysis. Neuroradiology 2012;54:929–938. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Bauckneht M, Picco A, Nobili F, et al. Amyloid positron emission tomography and cognitive reserve. World J Radiol 2015;28(7):475–483. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Robertson IH. A noradrenergic theory of cognitive reserve: implications for Alzheimer's disease. Neurobiol Aging 2013;34:298–308. [DOI] [PubMed] [Google Scholar]
- 52. Shalev N, Brosnan MB, Chechlacz M. Right lateralized brain reserve offsets age‐related deficits in ignoring distraction. Cereb Cortex Commun 2020;1:1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Szucs D, Ioannidis JP. Sample size evolution in neuroimaging research: an evaluation of highly‐cited studies (1990‐2012) and of latest practices (2017‐2018) in high‐impact journals. Neuroimage 2020;1(221):117164. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
FIG. S1. Voxelwise differences in the [18F]‐Fluorodeoxyglucose PET‐MR scan between healthy controls and PD subjects. Data are thresholded at uncorrected P < 0.001, FWE corrected at cluster level P < 0.05.
FIG. S2. Positive correlations between cognitive reserve score and [18F]‐Fluorodeoxyglucose PET uptake in PD subjects. (Uncorrected P < 0.001, FWE corrected at cluster level P < 0.05), projected onto the right‐hemisphere cortical surface of a template in MNI space.
TABLE S1. Clinical and demographic data. Data are presented as mean (standard deviation) or frequency (number). CR, Cognitive Reserve; CRQ, Cognitive Reserve Questionnaire, MDS‐UPDRS III, Movement Disorder Society‐Unified Parkinson's Disease Rating Scale part III. *p < 0.05 vs Healthy Controls; #P < 0.05 vs Superior CR.
TABLE S2. Brain regions showing differences in amyloid load and metabolic load between low‐medium and superior cognitive reserve groups.
TABLE S3. Brain regions with significant positive correlation between glucose metabolism and cognitive reserve.